from onnx import onnx_ml_pb2 as _onnx_ml_pb2 from google.protobuf.internal import containers as _containers from google.protobuf.internal import enum_type_wrapper as _enum_type_wrapper from google.protobuf import descriptor as _descriptor from google.protobuf import message as _message from typing import ClassVar as _ClassVar, Iterable as _Iterable, Mapping as _Mapping, Optional as _Optional, Union as _Union DESCRIPTOR: _descriptor.FileDescriptor class SequenceProto(_message.Message): __slots__ = ("name", "elem_type", "tensor_values", "sparse_tensor_values", "sequence_values", "map_values", "optional_values") class DataType(int, metaclass=_enum_type_wrapper.EnumTypeWrapper): __slots__ = () UNDEFINED: _ClassVar[SequenceProto.DataType] TENSOR: _ClassVar[SequenceProto.DataType] SPARSE_TENSOR: _ClassVar[SequenceProto.DataType] SEQUENCE: _ClassVar[SequenceProto.DataType] MAP: _ClassVar[SequenceProto.DataType] OPTIONAL: _ClassVar[SequenceProto.DataType] UNDEFINED: SequenceProto.DataType TENSOR: SequenceProto.DataType SPARSE_TENSOR: SequenceProto.DataType SEQUENCE: SequenceProto.DataType MAP: SequenceProto.DataType OPTIONAL: SequenceProto.DataType NAME_FIELD_NUMBER: _ClassVar[int] ELEM_TYPE_FIELD_NUMBER: _ClassVar[int] TENSOR_VALUES_FIELD_NUMBER: _ClassVar[int] SPARSE_TENSOR_VALUES_FIELD_NUMBER: _ClassVar[int] SEQUENCE_VALUES_FIELD_NUMBER: _ClassVar[int] MAP_VALUES_FIELD_NUMBER: _ClassVar[int] OPTIONAL_VALUES_FIELD_NUMBER: _ClassVar[int] name: str elem_type: int tensor_values: _containers.RepeatedCompositeFieldContainer[_onnx_ml_pb2.TensorProto] sparse_tensor_values: _containers.RepeatedCompositeFieldContainer[_onnx_ml_pb2.SparseTensorProto] sequence_values: _containers.RepeatedCompositeFieldContainer[SequenceProto] map_values: _containers.RepeatedCompositeFieldContainer[MapProto] optional_values: _containers.RepeatedCompositeFieldContainer[OptionalProto] def __init__(self, name: _Optional[str] = ..., elem_type: _Optional[int] = ..., tensor_values: _Optional[_Iterable[_Union[_onnx_ml_pb2.TensorProto, _Mapping]]] = ..., sparse_tensor_values: _Optional[_Iterable[_Union[_onnx_ml_pb2.SparseTensorProto, _Mapping]]] = ..., sequence_values: _Optional[_Iterable[_Union[SequenceProto, _Mapping]]] = ..., map_values: _Optional[_Iterable[_Union[MapProto, _Mapping]]] = ..., optional_values: _Optional[_Iterable[_Union[OptionalProto, _Mapping]]] = ...) -> None: ... class MapProto(_message.Message): __slots__ = ("name", "key_type", "keys", "string_keys", "values") NAME_FIELD_NUMBER: _ClassVar[int] KEY_TYPE_FIELD_NUMBER: _ClassVar[int] KEYS_FIELD_NUMBER: _ClassVar[int] STRING_KEYS_FIELD_NUMBER: _ClassVar[int] VALUES_FIELD_NUMBER: _ClassVar[int] name: str key_type: int keys: _containers.RepeatedScalarFieldContainer[int] string_keys: _containers.RepeatedScalarFieldContainer[bytes] values: SequenceProto def __init__(self, name: _Optional[str] = ..., key_type: _Optional[int] = ..., keys: _Optional[_Iterable[int]] = ..., string_keys: _Optional[_Iterable[bytes]] = ..., values: _Optional[_Union[SequenceProto, _Mapping]] = ...) -> None: ... class OptionalProto(_message.Message): __slots__ = ("name", "elem_type", "tensor_value", "sparse_tensor_value", "sequence_value", "map_value", "optional_value") class DataType(int, metaclass=_enum_type_wrapper.EnumTypeWrapper): __slots__ = () UNDEFINED: _ClassVar[OptionalProto.DataType] TENSOR: _ClassVar[OptionalProto.DataType] SPARSE_TENSOR: _ClassVar[OptionalProto.DataType] SEQUENCE: _ClassVar[OptionalProto.DataType] MAP: _ClassVar[OptionalProto.DataType] OPTIONAL: _ClassVar[OptionalProto.DataType] UNDEFINED: OptionalProto.DataType TENSOR: OptionalProto.DataType SPARSE_TENSOR: OptionalProto.DataType SEQUENCE: OptionalProto.DataType MAP: OptionalProto.DataType OPTIONAL: OptionalProto.DataType NAME_FIELD_NUMBER: _ClassVar[int] ELEM_TYPE_FIELD_NUMBER: _ClassVar[int] TENSOR_VALUE_FIELD_NUMBER: _ClassVar[int] SPARSE_TENSOR_VALUE_FIELD_NUMBER: _ClassVar[int] SEQUENCE_VALUE_FIELD_NUMBER: _ClassVar[int] MAP_VALUE_FIELD_NUMBER: _ClassVar[int] OPTIONAL_VALUE_FIELD_NUMBER: _ClassVar[int] name: str elem_type: int tensor_value: _onnx_ml_pb2.TensorProto sparse_tensor_value: _onnx_ml_pb2.SparseTensorProto sequence_value: SequenceProto map_value: MapProto optional_value: OptionalProto def __init__(self, name: _Optional[str] = ..., elem_type: _Optional[int] = ..., tensor_value: _Optional[_Union[_onnx_ml_pb2.TensorProto, _Mapping]] = ..., sparse_tensor_value: _Optional[_Union[_onnx_ml_pb2.SparseTensorProto, _Mapping]] = ..., sequence_value: _Optional[_Union[SequenceProto, _Mapping]] = ..., map_value: _Optional[_Union[MapProto, _Mapping]] = ..., optional_value: _Optional[_Union[OptionalProto, _Mapping]] = ...) -> None: ...